The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Satellite-based digital imaging can be extremely useful in agricultural. Satellite images of particular fields can be used to provide farmers with vegetation maps as well as assess problems within a field, such as nitrogen stress. Often, it is useful to provide a farmer with frequent satellite images of a field managed by the farmer. Unfortunately, some sources of satellite images may not provide images frequently enough to be useful to a farmer in identifying problems during the growing season. Thus, satellite images from a first source may be supplemented with satellite images from one or more other sources.
Using satellite images from different sources presents problems, however. A first problem is with image resolution. A first source may be able to provide images at a five meter resolution while a second source may only be able to provide images at 20 meter (m) resolution. While the 20 m resolution images may be interpolated onto a five meter resolution image grid, the resulting image would still miss a large amount of detail that was shown in the five meter resolution images. The differences in the two images may create the illusion of changes in the field that are not there.
A second problem in using satellite images from different sources is that various satellites use different ranges of frequencies for a particular frequency band. The frequency bands refer to a range of frequencies of light used by a satellite to produce an image. Satellites may include frequency bands for blue, green, red, near infrared, and infrared frequencies of light. As there is no uniformity in the definitions of each frequency band, various satellites may use different ranges of frequencies in their frequency bands. For example, a green frequency band for a first satellite may include frequencies of 520-590 nm while the green frequency band for a second satellite may include frequencies of 525-600 nm. These differences can cause a shift in the produced images, thereby creating the illusion of changes in the field that are not there.
A third problem in using satellite images from different sources is the availability of certain types of information from each source. For example, a first source of satellite images may be generated without a particular frequency band, such as a blue frequency band. When comparing multiple images, images produced with the blue frequency band would look very different from images produced without the blue frequency band.
Thus, there is a need for generating uniform images of a single type from images of different types. Additionally, there is a need for a method of generating high resolution images from low resolution images that contain the same levels of detail and patterns as received high resolution images of the same location.